revert: 移除 2:4 稀疏（PCOC 2.067 + 耗时反增 265s，to_sparse_semi_structured 与 nn.Linear 不兼容）

回退到稳定版：FP16 + Flash Attention + inference_mode（57.45 分）

代码/code/infer.py

@@ -511,28 +511,7 @@ def load_model(ckpt_path, device='cuda:0'):
 
     model.to(dev)
     model.eval()
-
-    # === 2:4 结构化稀疏：所有 Linear 层权重剪枝，A800 原生 2x 加速 ===
-    try:
-        sp_count = 0
-        for name, module in model.named_modules():
-            if isinstance(module, nn.Linear) and module.weight.dim() == 2:
-                w = module.weight.data
-                shape = w.shape
-                # 每 4 个连续元素保留幅度最大的 2 个
-                w_flat = w.reshape(-1, 4)
-                _, top_idx = torch.topk(w_flat.abs(), k=2, dim=1)
-                mask = torch.zeros_like(w_flat)
-                mask.scatter_(1, top_idx, 1.0)
-                pruned = (w_flat * mask).reshape(shape)
-                # 转为半结构化稀疏格式（A800 SM80 硬件加速）
-                module.weight = nn.Parameter(
-                    torch.sparse.to_sparse_semi_structured(pruned)
-                )
-                sp_count += 1
-        print(f"[INFO] 2:4 sparsity applied to {sp_count} Linear layers")
-    except Exception as e:
-        print(f"[WARNING] 2:4 sparsity failed ({e}), continuing with dense weights")
+    print(f"[INFO] Model ready. Device: {dev}")
 
     return model, dev